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Offshore Wind Energy and Grid Integration

The main objective of the proposed Energy Frontier Research is to enable cost-effective, environment-friendly, reliable, and resilient grid operation with increasing penetration of offshore wind power through coupled novel observations and enhanced environmental and power system integration modeling capabilities.

Topic Area 1 Grid Reliability with Increased Wind Integration

Wind systems integration requires analysis and validation to ensure reliable and resilient grid operation with increasing wind power plants.

  • Risk analysis and uncertainty assessment tools: wind, solar and load forecasts are always subject to uncertainties. There are also uncertainties associated with wind control models, such as inappropriate parameters and control modes. This calls for the development of new risk and uncertainty assessment tools that turn the look-ahead probabilistic forecast errors of wind, solar and loads and model uncertainties into actional information for the system operator. There is a critical need of developing quantitative metrics in assessing how proprietary wind model uncertainties can affect system planning and operation.
  • Risk-Aware Operation and Decision Making: Based on the risk assessment outcomes, risk-aware system operation/decision-making tools are needed for mitigation while minimizing the costs.
  • Small signal stability analysis tool with blackbox IBR models: the small-signal stability analysis usually requires a detailed system model with proper linearization. This may not be available given that IBRs/wind generation models are owned by vendors. Thus, advanced small-signal stability tools that respect the blackbox nature of IBRs are needed.

Topic Area 2 Analytics for Monitoring and Control

  • Inertia quantification and fast frequency reserve forecasting tools: The inertial response from WPPs is dependent on controllers and their operating conditions. For example, the mechanical torque applied by the wind turbine to the generator shaft during an inertial response suffers influence from the pitch control, the drive-train control, and wind variations. Hence, the inertial response of a WPP is time-varying. This characteristic differs sharply from synchronous generators, whose mechanical torque remains constant for a significant time window because of the turbine-governor system’s slow response. This requires new tools for quantifying the effective, time-varying inertia from WPPs and other IBRs with grid-following and grid-forming control modes.
  • Wind and other IBR model validation and calibration tools: the wind and IBR models and their controllers are frequently subject to errors as the vendor or manufacture models have been found to have inconsistencies with actual system responses. Model validation and calibration tools have been widely used for synchronous generators, but the models of wind and other IBRs are proprietary, i.e., black-box models for utilities, leading to huge challenges for model calibrations. This calls for the development of novel model validation and calibration tools.
  • Transmission and distribution co-simulator using the RTDS: studying the interactions between transmission and distribution systems considering increased inverter-based resources (IBRs) is essential for system planning and operation. The T&D co-simulator allows us to investigate the impacts of IBRs at the distribution systems on the bulk system responses as well as the disturbances of the bulk systems on the distribution system IBRs, such as fault ride-through, protection coordination, and control.

Topic Area 3 Offshore Wind Resource Characterization and Forecasting

To enhance wind power integration in the distribution grid for utility-scale offshore wind energy systems, uncertainty associated with wind resources and operating conditions must be reduced and fidelity of short-term forecasts should be enhanced. Key elements of metocean information required to improve the predictability of power generation by offshore wind projects include: (i) observations of the spatiotemporal variability of the vertical profiles of wind and turbulent kinetic energy; (ii) characterization of the dynamic interactions of wind, waves, ocean heat content, and windfarm turbines; (iii) improved wind forecasting skill at hub-height and across the rotor plane for time scales ranging from a half-hour to days.

  • Improve offshore wind forecasting: Acquire observations to enable the advancement and validation of Weather Research and Forecasting (WRF) model capabilities to forecast hub height and rotor equivalent wind speed as well as shear and veer across the rotor plane for operational wind power forecasts.
  • Demonstrate wind forecasting for grid integration: Conduct demonstration studies of forecast accuracy, uncertainty quantification, and forecast reliability for power integration efficiency. Based on this work develop a probabilistic framework based on improved WRF offshore wind parameterizations for wind power forecasts.

Points of Contact

Eversource Energy Center | Innovation Partnership Building: 159 Discovery Drive, Unit 5276, Storrs, CT 06269-5276 | E-Mail: eversourceenergycenter@uconn.edu